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MV Stats News

Vol. 3, Number 1, September 29, 2015. MV Stats News. Bringing multivariate data analysis and data visualization to your breakfast table. Today’s topic: Economists use “intention-to-treat” methodology to assess Quebec childcare outcomes, claiming negative effects.

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MV Stats News

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  1. Vol. 3, Number 1, September 29, 2015 MV Stats News Bringing multivariate data analysis and data visualization to your breakfast table Today’s topic: Economists use “intention-to-treat” methodology to assess Quebec childcare outcomes, claiming negative effects Michael Friendly, Staff Reporter Filed: 1/2/2020 1:08 PM

  2. Background: BGM Study • A recent working paper by economists Michael Baker, Jon Gruber & Michael Milligan (BGM) studied outcomes of children in Quebec on cognitive and non-cognitive (health, life satisfaction, crime rates) measures before and after the introduction of the universal $5/day childcare system in that province. • They conclude that “cohorts with increased childcare access subsequently had worse health, lower life satisfaction and higher crime rates later in life.” • Given that this is a hot topic in the current election, what should we make of these findings?

  3. BGM methodology • Data: Statistics Canada’s National Longitudinal Study of Children and Youth (NLSCY) • Five waves of data, from 1994-95 to 2002-03 • Sample of ~ 2000 kids per wave and age (0-4, two-parent families) • Subsidized childcare ($5/day) phased in starting 1997

  4. Outcome measures • Childcare (binary) – any type of non-paternal care • Non-cognitive child behavior scores – hyperactivity, anxiety, aggression, … • Other data sets: • School achievement (SAIP, PISA) • Health & well-being (CC Health survey) • Criminal behavior (Canada Uniform Reporting Survey)

  5. Analysis strategy • “Difference-in-difference” analysis • (ypost – ypre)Quebec - (ypost – ypre)Rest • Fit regression models: yipt = α + βexposurept + πprovincep + δyeart + λXiptεipt • Exposure: 0/1 (“to Quebec childcare”) • Province, year (0/1 dummies) • X: other control variables (gender, age, mother’s education, …)

  6. Sample results

  7. Sample results

  8. Claims • This analysis provides the basis for a causal interpretation: “exposure” to daycare → negative outcomes. • Not a randomized experiment, but rather a “natural experiment” • Appeals to parallel with “intention to treat” analysis often used in clinical trials

  9. What’s wrong with this picture? • Contradicts huge literature showing that it is daycare quality that affects outcomes • Concept of “exposure” (universal program in Quebec) cannot relate to individuals • Doesn’t study children actually enrolled • Not longitudinal– different samples from year to year • Results could equally be attributed to children NOT enrolled in childcare • “Intention-to-treat” analogy for causal inference has no bearing here.

  10. Sources & references • Various papers by BGM: • http://faculty.arts.ubc.ca/kmilligan/research/childcare.htm • Commentary: • Margaret Wente: “The daycare brawl…” http://www.theglobeandmail.com/globe-debate/article26548245.ece • Goelman et al: “What Canadians Need to Know About Good Quality Child Care” http://earlylearning.ubc.ca/media/publications/2006_goelman_what_canadians_need_to_know_responsetokevinmilligan.pdf --- 30 ---

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